bib-enrich-mcp 0.1.0

MCP Server for fixing and enriching BibTeX bibliography metadata

bib-enrich-mcp

An MCP (Model Context Protocol) server that fixes and enriches BibTeX bibliography files with metadata from academic sources like arXiv, DBLP, and CrossRef.

Features

• Automatic metadata scraping from multiple sources:
  • arXiv API
  • DBLP API
  • CrossRef API
• BibTeX parsing and writing with full field support
• Batch processing of entire .bib files
• MCP integration for use with AI assistants

Installation

# Install with uv tool
uv tool install bib-enrich-mcp

# Or clone and install locally
git clone https://github.com/your-username/bib-enrich-mcp.git
cd bib-enrich-mcp
uv sync

Usage

As an MCP Server

Add to your MCP client configuration:

{
  "mcpServers": {
    "bib-fix": {
      "command": "bib-enrich-mcp"
    }
  }
}

Running the Server

bib-enrich-mcp

API Documentation

MCP Tools

mcp_enrich_bib_entry

Enrich a single bibliography entry by scraping metadata from academic sources.

Parameters:

• cite_key (required): The citation key for the entry
• title (optional): Paper title to search for
• arxiv_id (optional): arXiv ID (e.g., "2401.12345")
• doi (optional): DOI of the paper

Returns: BibTeX string with enriched metadata

Example:

result = await mcp_enrich_bib_entry(
    cite_key="vaswani2017attention",
    title="Attention Is All You Need"
)

mcp_enrich_bib_file

Enrich all entries in a BibTeX file.

Parameters:

• file_path (required): Path to the .bib file

Returns: Summary of enriched entries

Example:

result = await mcp_enrich_bib_file("/path/to/references.bib")
# Returns: "Enriched 5/10 entries in /path/to/references.bib"

Python API

You can also use the library directly in Python:

from bib_enrich_mcp.bib_parser import parse_bib_file, write_bib_file
from bib_enrich_mcp.scrapers import scrape_metadata

# Parse a bib file
entries = parse_bib_file("references.bib")

# Scrape metadata for a paper
results = await scrape_metadata(
    title="Attention Is All You Need",
    arxiv_id="1706.03762"
)

Supported Metadata Sources

Source	Search by Title	Search by ID	Notes
arXiv	✅	✅ (arXiv ID)	Best for preprints
DBLP	✅	❌	Best for CS conferences
CrossRef	✅	✅ (DOI)	Best for journals

Development

Running Tests

uv run pytest tests/ -v

Project Structure

bib-enrich-mcp/
├── src/bib_enrich_mcp/
│   ├── __init__.py
│   ├── bib_parser.py    # BibTeX parsing/writing
│   ├── scrapers.py      # Metadata scrapers
│   └── server.py        # MCP server
├── tests/
│   ├── test_bib_parser.py
│   ├── test_scrapers.py
│   └── test_server.py
├── pyproject.toml
└── README.md

License

MIT